Executive summary From the short-term and long-term effects of the COVID-19 pandemic to
the health insecurities brought about by climate change, health futures are unfolding in an …

There has been much research effort expended toward the use of Bayesian networks (BNs)
in medical decision-making. However, because of the gap between developing an accurate …

The “learning health system”(LHS) concept has been defined in broad terms, which makes it
challenging for health system leaders to determine exactly what is required to transform their …

Introduction Learning health systems (LHS) is a multifaceted subject. This paper reviewed
current concepts as well as real-world experiences of LHS, drawing on published and …

This article describes how the T1D Exchange Quality Improvement Collaborative leverages
an innovative web platform, the QI Portal, to gather and store electronic medical record …

Clinical decision-making is based on knowledge, expertise, and authority, with clinicians
approving almost every intervention—the starting point for delivery of “All the right care, but …

Objectives Learning health systems (LHS) integrate knowledge and practice through cycles
of continuous quality improvement and learning to increase healthcare quality. LHS have …

Abstract Introduction First Nations, Inuit, and Métis (FNIM) peoples experience systemic
health disparities within Ontario's healthcare system. Learning health systems (LHS) is a …

Data mining is a powerful tool to reduce costs and mitigate errors in the diagnostic analysis
and repair of complex engineered system, but it has yet to be applied systematically to the …

Objective Despite the benefits of the tailored drug–drug interaction (DDI) alerts and the
broad dissemination strategy, the uptake of our tailored DDI alert algorithms that are …